Model-free control refers to a type of control strategy that operates without an explicit model of the system dynamics. This approach is especially relevant in complex systems like soft robotics, where obtaining an accurate model can be challenging due to their highly nonlinear and often unpredictable behavior. Instead of relying on a model, model-free control methods utilize data-driven techniques and reinforcement learning to make decisions and adjust actions based on the feedback from the environment.
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